Updated on 02/02/2023
Big Data in retail distribution: an introduction
In retail distribution, Big Data is a formidable resource. The advantages range from personalizing offers to more efficient store management. Achieving these benefits require that some conditions must be met.
Big Data in is an incredible resource to evolve and grow a business like that retail distribution which, as we saw in our previous blog post, is often used too conservatively.
More than any other point in time, today, large amounts of data can be collected and processed in order to provide a useful and understandable picture of your business. Let’s start with a definition.
The Big Data
Although the concept is not new, it’s worthwhile to start with a definition of Big Data. As often happens, with the passage of time the expression has begun to be used with a different meaning.
“Big Data” can, for example, indicate the great speed with which data is currently generated, or the growing capacity of software and companies to store it, or the increasingly refined systems for ordering and interpreting it (ibmbigdatahub.com).
In essence, just two words for many meanings, but ultimately, what do we mean when we talk about Big Data?
According to Gartner, “Big data is high-volume, high-velocity and/or high-variety information assets that demand cost-effective, innovative forms of information processing that enable enhanced insight, decision making, and process automation” (gartner.com). On closer inspection, within this definition there is a summary of the right approach, the best ways and the main benefits that retail distribution should have when dealing with Big Data.
What is Big Data in the world of retail distribution?
First of all, it could be said that in the context of retail distribution, Big Data is all the information that a department store, a shopping mall, or any other player in the sector can obtain about its consumers.
The methods of collection are different and can be both online and offline. For example, as far as analog methods are concerned, it is possible to use paper questionnaires, through paper forms or using touch points placed inside the store, to collect information on customers. Alternatively, loyalty programs can also be used to collect relevant information about customer consumption habits and preferences.
However, this is not the only Big Data that retailer can exploit.
Big Data can improve the supply chain
Big data, in fact, can also come from other components of the business, which are equally strategic for making it sustainable or even competitive. Think, for example, of the warehouse: it is an enormous source of Big Data, whose efficient management is an essential condition to improve its performance and the customer experience.
Through the Internet Of Things, in fact, it is possible to monitor the entry and exit of goods and combine it with the sales trends of certain periods. In this way, the business can better control its stock and prepare the supply chain so that they can cope with peaks in demand without leaving empty shelves at less opportune times.
In addition, Big Data also makes it possible to make strategic decisions that go beyond the management of the individual store. If properly collected and arranged, this information even provides the possibility to hypothesize the financial impact that opening a new store could have on an existing one.
In essence, knowing how to use the information available and make it intelligible allows you to make forward-looking choices for your business.
Big Data at the service of the Customer Experience
However, let’s be clear: although these are all very good ways that Big Data can be used in distribution retail, this resource is especially important to improve the consumer’s in-store experience.
This benefit is far from negligible given that the ability to attract new consumers is a particularly sensitive issue when it comes to large retailers in Italy and abroad. Just think, for example, of what happened in the last few years to American department stores, which have seen a drastic reduction in the number of customers, with the consequent closure of many physical stores and the cancellation of more than 100,000 jobs. Such a phenomenon has involved not only local players, but also global players operating in the retail sector (for example, American Apparel or Abercrombie & Fitch), demonstrating that no one can feel protected or excluded from this possibility.
Also, because at the base of this “apocalypse,” which for now has spared Italy, there are deeper reasons, which concern the change in consumers’ habits and their expectations about their desired in-store shopping experience (datamanager.it). These new habits have spread even more precisely during the recent Covid-19 health emergency. One of the most surprising and unexpected effects of the pandemic has been the rediscovery by all Italians of the “neighborhood shop”, not only as a safer supply point for avoiding large crowds, but above all as places where customers could start shopping on a daily basis for everything they need (fortuneita.com).
The reasons for these behavioral changes are linked to several factors: they range from the renewed perception of the importance of the city, the local environment, to the willingness to support local businesses who are facing financial difficulties as a result of the lockdown. Today, distribution retailers must be concerned about the consequences of these changes (italiaoggi.it).
One is predictable, namely that more and more consumers will look for places with smaller crowds and more personalized shopping experiences, such as those that can be found in small shops. Precisely in this sense, Big Data can become a considerable resource for all major players in adequately responding to these new trends.
With Big Data, the Customer Experience becomes personalized
Big Data in retail distribution allows you to know more and more about your customers and to react accordingly.
For example, if interpreted correctly, Big Data can provide important information about certain “consumption patterns” during the year and companies can use this data to manage the supply chain and organize the internal layout of physical stores in order to provide the most popular products, placing them in strategic points that draw the attention of consumers. But you can go even further, enriching and innovating a marketing tool that is a bit outdated but still much loved by all retail operators: namely promotional campaigns. Big Data can be used to propose hyper-personalized offers to consumers, based on their preferences and habits.
Macy’s, one of the brands who have experienced the “retail apocalypse” mentioned above, has opened up to the digital experience, reaching consumers with newsletters and offers that are only accessible from digital platforms. In just a short time, Macy’s saw incredible results: a 125% increase in sales.
In addition, by collecting feedback and reactions from users, Macy’s was able to accurately profile its consumers and make its offers and promotions even more precise and tailored to customers, both in terms of content and timing.
A personalized video for a personalized offer
Such a result, which is already remarkable, especially considering the context in which it was achieved, could be further enhanced with personalized communications. After all, each day, customers are reached day by a huge amount of stimuli and only a few manage to actually attract their attention. So, in order to make the promotion really effective, Big Data should be used to personalize the communication of the offers, so that the consumer feels that he or she is at the center of a shopping experience that is tailored to the customer and his or her needs.
An example of these personalized communications is Doxee Pvideo®, an innovative product developed by Doxee.
Doxee Pvideo® content can be personalized according to the type of message you want to convey and according to the user you want to reach. The level of content personalization is very high; in fact, each of the video components can be created according to the recipient’s data. For example, it is possible to insert specific text elements that integrate perfectly with the content of the video; in addition, you can also customize the audio clips in order to make the video content more immersive and interesting.
In the context of retail distribution, video can be used in innovative marketing strategies, perhaps by inserting it into loyalty campaigns or to enrich the customer loyalty program by making communications more engaging. That’s not all: Doxee’s personalized videos can also be used to make users better acquainted with the company’s brand equity initiatives, which are particularly important from a marketing point of view because they represent an added value that consumers often look for.
How? Through personalized narration, which is possible within each Doxee Pvideo®. In fact, thanks to the Dynamic Storyboard, each recipient can decide how to modify the narrative flow of the content, depending on the answers or choices he makes during the viewing.
In other words, the video can be manipulated directly by the recipient, who chooses which parts to watch and which parts to skip according to their interests and priorities. Among other things, all of this takes place directly within the video, which is a great advantage since it makes navigation more comfortable and intuitive. In this way, a consumer who is more attentive to environmental sustainability can be reached by a communication about the green initiatives of that particular retailer and will then have the opportunity to choose the initiatives that he’s more interested in and receive a special offer for eco-friendly products.
The same can also happen for another consumer who may be interested in the sustainability of the supply chain, who may be given the opportunity, within the video, to access offers for locally produced products.
Big Data also improves the in-store experience
Among other things, in doing so, operators are able to make use of an innovative tool to effectively attract consumers into physical stores, while at the same time satisfying the ever-increasing demand for an omnichannel experience by consumers themselves. Omnichannel has now become an indispensable part of a modern customer experience. Big Data can help improve the Customer Experience even in the physical retail store.
From this point of view, the Italian department store La Rinascente is a perfect example. For some time now, area supervisors have been using specific tablets and software to monitor customers and intervene promptly when there are critical issues or specific needs (source: digital4.biz). In this way, the shopping experience can be modeled in real time, based on customer behavior up to the moment.
This, of course, requires the adoption of special digital tools as well as specific training for the workforce, which must be able to manage these types of solutions by integrating them into everyday tasks. As the La Rinascente example shows, forward-looking strategies can have positive results.
